%image of weather regimes
@online{weather_regimes,
    Author = {Weather and Climate at Reading},
    title = {Weather Regimens Visualization},
    Lastchecked = {01.12.2021},
    url   = {http://blogs.reading.ac.uk/weather-and-climate-at-reading/2020/recent-progress-in-simulating-north-atlantic-weather-regimes/},
}

@online{vae_image,
    Author = {LearnOpenCV},
    title = {Variational Autoencoder in TensorFlow},
    Lastchecked = {01.12.2021},
    url = {https://learnopencv.com/variational-autoencoder-in-tensorflow/}
}

@article{ae_image,
AUTHOR = {Elbattah, Mahmoud and Loughnane, Colm and Guérin, Jean-Luc and Carette, Romuald and Cilia, Federica and Dequen, Gilles},
TITLE = {Variational Autoencoder for Image-Based Augmentation of Eye-Tracking Data},
JOURNAL = {Journal of Imaging},
VOLUME = {7},
YEAR = {2021},
NUMBER = {5},
ARTICLE-NUMBER = {83},
URL = {https://www.mdpi.com/2313-433X/7/5/83},
ISSN = {2313-433X},
ABSTRACT = {Over the past decade, deep learning has achieved unprecedented successes in a diversity of application domains, given large-scale datasets. However, particular domains, such as healthcare, inherently suffer from data paucity and imbalance. Moreover, datasets could be largely inaccessible due to privacy concerns, or lack of data-sharing incentives. Such challenges have attached significance to the application of generative modeling and data augmentation in that domain. In this context, this study explores a machine learning-based approach for generating synthetic eye-tracking data. We explore a novel application of variational autoencoders (VAEs) in this regard. More specifically, a VAE model is trained to generate an image-based representation of the eye-tracking output, so-called scanpaths. Overall, our results validate that the VAE model could generate a plausible output from a limited dataset. Finally, it is empirically demonstrated that such approach could be employed as a mechanism for data augmentation to improve the performance in classification tasks.},
DOI = {10.3390/jimaging7050083}
}

%CDS
@online{climate_data_store,
    Author = {Copernicus - Climate Data Store},
    title = {Climate Data Store},
    Lastchecked = {01.12.2021},
    url = {https://cds.climate.copernicus.eu/cdsapp\#!/home}
}

%ERA 5
@article{hersbach2020era5,
  title={The ERA5 global reanalysis},
  author={Hersbach, Hans and Bell, Bill and Berrisford, Paul and Hirahara, Shoji and Hor{\'a}nyi, Andr{\'a}s and Mu{\~n}oz-Sabater, Joaqu{\'\i}n and Nicolas, Julien and Peubey, Carole and Radu, Raluca and Schepers, Dinand and others},
  journal={Quarterly Journal of the Royal Meteorological Society},
  volume={146},
  number={730},
  pages={1999--2049},
  year={2020},
  publisher={Wiley Online Library}
}

@online{era5,
    Author = {Copernicus - Climate Data Store},
    title = {ERA5 hourly data on pressure levels from 1979 to present},
    Lastchecked = {01.12.2021},
    url = {https://cds.climate.copernicus.eu/cdsapp\#!/dataset/reanalysis-era5-pressure-levels}
}

%ECMWF S2S
@article {p17442,
	title = {New clustering products},
	issue = {127},
	year = {2011},
	pages = {6-11},
	publisher = {ECMWF},
	type = {Meteorology},
	chapter = {Meteorology},
	keywords = {newsletter},
	doi = {10.21957/lr3bcise},
	url = {https://www.ecmwf.int/node/17442},
	author = {Laura Ferranti and Corti, S.}
}

%regimes
@article{strauss,
author = {Straus, David and Corti, Susanna and Molteni, Franco},
year = {2007},
month = {05},
pages = {2251-},
title = {Circulation Regimes: Chaotic Variability versus SST-Forced Predictability},
volume = {20},
journal = {Journal of Climate},
doi = {10.1175/JCLI4070.1}
}

%cassou et al 4 CLUSTERS but also 5 CLUSTERS
@article{2011ClDy...36...19C,
       author = {{Cassou}, Christophe and {Minvielle}, Marie and {Terray}, Laurent and {P{\'e}rigaud}, Claire},
        title = "{A statistical-dynamical scheme for reconstructing ocean forcing in the Atlantic. Part I: weather regimes as predictors for ocean surface variables}",
      journal = {Climate Dynamics},
     keywords = {Weather regimes, Climate variability, Atlantic Ocean, Oceanic forcing variables},
         year = 2011,
        month = jan,
       volume = {36},
       number = {1-2},
        pages = {19-39},
          doi = {10.1007/s00382-010-0781-7},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2011ClDy...36...19C},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

%effectiveness of sub-seasonal predictions SUBSEASONAL FORECASTS
@article{https://doi.org/10.1002/met.1654,
author = {White, Christopher J. and Carlsen, Henrik and Robertson, Andrew W. and Klein, Richard J.T. and Lazo, Jeffrey K. and Kumar, Arun and Vitart, Frederic and Coughlan de Perez, Erin and Ray, Andrea J. and Murray, Virginia and Bharwani, Sukaina and MacLeod, Dave and James, Rachel and Fleming, Lora and Morse, Andrew P. and Eggen, Bernd and Graham, Richard and Kjellström, Erik and Becker, Emily and Pegion, Kathleen V. and Holbrook, Neil J. and McEvoy, Darryn and Depledge, Michael and Perkins-Kirkpatrick, Sarah and Brown, Timothy J. and Street, Roger and Jones, Lindsey and Remenyi, Tomas A. and Hodgson-Johnston, Indi and Buontempo, Carlo and Lamb, Rob and Meinke, Holger and Arheimer, Berit and Zebiak, Stephen E.},
title = {Potential applications of subseasonal-to-seasonal (S2S) predictions},
journal = {Meteorological Applications},
volume = {24},
number = {3},
pages = {315-325},
keywords = {climate prediction, forecasting, decision-support, ensemble forecasts, extremes, extended-range, seasonal prediction},
doi = {https://doi.org/10.1002/met.1654},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/met.1654},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/met.1654},
abstract = {ABSTRACT While seasonal outlooks have been operational for many years, until recently the extended-range timescale referred to as subseasonal-to-seasonal (S2S) has received little attention. S2S prediction fills the gap between short-range weather prediction and long-range seasonal outlooks. Decisions in a range of sectors are made in this extended-range lead time; therefore, there is a strong demand for this new generation of forecasts. International efforts are under way to identify key sources of predictability, improve forecast skill and operationalize aspects of S2S forecasts; however, challenges remain in advancing this new frontier. If S2S predictions are to be used effectively, it is important that, along with science advances, an effort is made to develop, communicate and apply these forecasts appropriately. In this study, the emerging operational S2S forecasts are presented to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. The value of applications-relevant S2S predictions is explored, and the opportunities and challenges facing their uptake are highlighted. It is shown how social sciences can be integrated with S2S development, from communication to decision-making and valuation of forecasts, to enhance the benefits of ‘climate services’ approaches for extended-range forecasting. While S2S forecasting is at a relatively early stage of development, it is concluded that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.},
year = {2017}
}

%wind-energy forecasting, renewables SUBSEASONAL FORECASTS
@article{Soret_2019,
	doi = {10.1088/1742-6596/1222/1/012009},
	url = {https://doi.org/10.1088/1742-6596/1222/1/012009},
	year = 2019,
	month = {5},
	publisher = {{IOP} Publishing},
	volume = {1222},
	pages = {012009},
	author = {A Soret and V Torralba and N Cortesi and I Christel and Ll Palma and A Manrique-Su{\~{n}}{\'{e}}n and Ll Lled{\'{o}} and N Gonz{\'{a}}lez-Reviriego and F J Doblas-Reyes},
	title = {Sub-seasonal to seasonal climate predictions for wind energy forecasting},
	journal = {Journal of Physics: Conference Series},
	abstract = {Both renewable energy supply and electricity demand are strongly influenced by meteorological conditions and their evolution over time in terms of climate variability and climate change. However, knowledge of power output and demand forecasting beyond a few days remains poor. Current methodologies assume that long-term resource availability is constant, ignoring the fact that future wind resources could be significantly different from the past wind energy conditions. Such uncertainties create risks that affect investment in wind energy projects at the operational stage where energy yields affect cash flow and the balance of the grid. Here we assess whether sub-seasonal to seasonal climate predictions (S2S) can skilfully predict wind speed in Europe. To illustrate S2S potential applications, two periods with an unusual climate behaviour affecting the energy market will be presented. We find that wind speed forecasted using S2S exhibits predictability some weeks and months in advance in important regions for the energy sector such as the North Sea. If S2S are incorporated into planning activities for energy traders, energy producers, plant operators, plant investors, they could help improve management climate variability related risks.}
}

%van der wiel clustering 4 CLUSTERS + QUANTIFICATION with DISTRIBUTIONS
@article{van_der_Wiel_2019,
	doi = {10.1088/1748-9326/ab38d3},
	url = {https://doi.org/10.1088/1748-9326/ab38d3},
	year = 2019,
	month = {9},
	publisher = {{IOP} Publishing},
	volume = {14},
	number = {9},
	pages = {094010},
	author = {K. {van der Wiel} and Hannah C Bloomfield and Robert W Lee and Laurens P Stoop and Russell Blackport and James A Screen and Frank M Selten},
	title = {The influence of weather regimes on European renewable energy production and demand},
	journal = {Environmental Research Letters},
	abstract = {The growing share of variable renewable energy increases the meteorological sensitivity of power systems. This study investigates if large-scale weather regimes capture the influence of meteorological variability on the European energy sector. For each weather regime, the associated changes to wintertime—mean and extreme—wind and solar power production, temperature-driven energy demand and energy shortfall (residual load) are explored. Days with a blocked circulation pattern, i.e. the ‘Scandinavian Blocking’ and ‘North Atlantic Oscillation negative’ regimes, on average have lower than normal renewable power production, higher than normal energy demand and therefore, higher than normal energy shortfall. These average effects hide large variability of energy parameters within each weather regime. Though the risk of extreme high energy shortfall events increases in the two blocked regimes (by a factor of 1.5 and 2.0, respectively), it is shown that such events occur in all regimes. Extreme high energy shortfall events are the result of rare circulation types and smaller-scale features, rather than extreme magnitudes of common large-scale circulation types. In fact, these events resemble each other more strongly than their respective weather regime mean pattern. For (sub-)seasonal forecasting applications weather regimes may be of use for the energy sector. At shorter lead times or for more detailed system analyses, their ineffectiveness at characterising extreme events limits their potential.}
}

%van der wiel MODELING ENERGY VARIABLES
@article{VANDERWIEL2019261,
title = {Meteorological conditions leading to extreme low variable renewable energy production and extreme high energy shortfall},
journal = {Renewable and Sustainable Energy Reviews},
volume = {111},
pages = {261-275},
year = {2019},
issn = {1364-0321},
doi = {https://doi.org/10.1016/j.rser.2019.04.065},
url = {https://www.sciencedirect.com/science/article/pii/S1364032119302862},
author = {K. {van der Wiel} and L.P. Stoop and B.R.H. {van Zuijlen} and R. Blackport and M.A. {van den Broek} and F.M. Selten},
keywords = {Variable renewable energy, Energy transition, Energy security, Extreme weather, Energy meteorology, Climate change, Climate impacts},
abstract = {To mitigate climate change a renewable energy transition is needed. Existing power systems will need to be redesigned to balance variable renewable energy production with variable energy demand. We investigate the meteorological sensitivity of a highly-renewable European energy system using large ensemble simulations from two global climate models. Based on 3×2000 years of simulated weather conditions, daily wind and solar energy yields, and energy demand are calculated. From this data, 1-, 7- and 14-days events of extreme low renewable energy production and extreme high energy shortfall are selected. Energy shortfall is defined as the residual load, i.e. demand minus renewable production. 1-day low energy production days are characterised by large-scale high pressure systems over central Europe, with lower than normal wind speeds. These events typically occur in winter when solar energy is limited due to short day lengths. Situations of atmospheric blocking lead to long lasting periods of low energy production, such 7- and 14-days low production events peak late summer. High energy shortfall events occur due to comparable high pressure systems though now combined with below normal temperatures, driving up energy demand. In contrast to the low energy production events, 1-, 7- and 14-days high shortfall events all occur mid-winter, locked to the coldest months of the year. A spatial redistribution of wind turbines and solar panels cannot prevent these high-impact events, options to import renewable energy from remote locations during these events are limited. Projected changes due to climate change are substantially smaller than interannual variability. Future power systems with large penetration of variable renewable energy must be designed with these events in mind.}
}

%sensitivity power systems and climate variability QUANTIFICATION ENERGY VARIABLES
@article{Bloomfield_2016,
	doi = {10.1088/1748-9326/11/12/124025},
	url = {https://doi.org/10.1088/1748-9326/11/12/124025},
	year = 2016,
	month = {12},
	publisher = {{IOP} Publishing},
	volume = {11},
	number = {12},
	pages = {124025},
	author = {Bloomfield and D J Brayshaw and L C Shaffrey and P J Coker and H E Thornton},
	title = {Quantifying the increasing sensitivity of power systems to climate variability},
	journal = {Environmental Research Letters},
	abstract = {Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.}
}

%6 clusters, k-means CLUSTERING WITH CONSTRAINTS + BIC SCORE + 4/6 CLUSTERS
@inproceedings{Falkena2020RevisitingTI,
  title={Revisiting the Identification of Winterƒtime Atmospheric Circulation Regimes in the Euro-Atlantic Sector},
  author={Swinda K. J. Falkena and J. D. Wiljes and A. Weisheimer and T. Shepherd},
  year={2020}
}

%7 CLUSTERS + QUANTIFICATION 
@article{grams,
author = {Grams, Christian and Beerli, Remo and Pfenninger, Stefan and Staffell, Iain and Wernli, Heini},
year = {2017},
month = {07},
pages = {},
title = {Balancing Europe’s wind-power output through spatial deployment informed by weather regimes},
volume = {7},
journal = {Nature Climate Change},
doi = {10.1038/nclimate3338}
}

%EOFS
@article{eof,
author = {Hannachi, Abdel},
year = {2004},
month = {04},
pages = {},
title = {A primer for EOF analysis of climate data}
}

%AUTOENCODER for CLIMATE DATA
@article{dim_red_AEs,
author = {Saenz, J. and Lubbers, N. and Urban, Nathan},
year = {2018},
month = {08},
pages = {},
title = {Dimensionality-Reduction of Climate Data using Deep Autoencoders}
}

%VAE for CLUSTERING
@article{DBLP:journals/corr/abs-2005-04613,
  author    = {Vignesh Prasad and
               Dipanjan Das and
               Brojeshwar Bhowmick},
  title     = {Variational Clustering: Leveraging Variational Autoencoders for Image
               Clustering},
  journal   = {CoRR},
  volume    = {abs/2005.04613},
  year      = {2020},
  url       = {https://arxiv.org/abs/2005.04613},
  archivePrefix = {arXiv},
  eprint    = {2005.04613},
  timestamp = {Thu, 14 May 2020 16:56:02 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2005-04613.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%SIGMA VAE
@misc{rybkin2020sigmavae,
    title={Simple and Effective VAE Training
    with Calibrated Decoders},
    author={Oleh Rybkin and Kostas Daniilidis
    and Sergey Levine},
    year={2020},
}
%BETA VAE
@inproceedings{Higgins2017betaVAELB,
  title={beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework},
  author={I. Higgins and L. Matthey and A. Pal and Christopher P. Burgess and Xavier Glorot and M. Botvinick and S. Mohamed and Alexander Lerchner},
  booktitle={ICLR},
  year={2017}
}


%DISENTANGLED REPRESENTATIONS - IDENTIFIABLE DOUBLE VAE
@misc{mita2021identifiable,
      title={An Identifiable Double VAE For Disentangled Representations}, 
      author={Graziano Mita and Maurizio Filippone and Pietro Michiardi},
      year={2021},
      eprint={2010.09360},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

%DISENTANGLED REPRESENTATIONS 
@article{DBLP:journals/corr/abs-1811-12359,
  author    = {Francesco Locatello and
               Stefan Bauer and
               Mario Lucic and
               Sylvain Gelly and
               Bernhard Sch{\"{o}}lkopf and
               Olivier Bachem},
  title     = {Challenging Common Assumptions in the Unsupervised Learning of Disentangled
               Representations},
  journal   = {CoRR},
  volume    = {abs/1811.12359},
  year      = {2018},
  url       = {http://arxiv.org/abs/1811.12359},
  archivePrefix = {arXiv},
  eprint    = {1811.12359},
  timestamp = {Fri, 30 Nov 2018 12:44:28 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1811-12359.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%DISENTANGLED REPRESENTATIONS 
@article{DBLP:journals/corr/abs-1905-13662,
  author    = {Francesco Locatello and
               Gabriele Abbati and
               Tom Rainforth and
               Stefan Bauer and
               Bernhard Sch{\"{o}}lkopf and
               Olivier Bachem},
  title     = {On the Fairness of Disentangled Representations},
  journal   = {CoRR},
  volume    = {abs/1905.13662},
  year      = {2019},
  url       = {http://arxiv.org/abs/1905.13662},
  archivePrefix = {arXiv},
  eprint    = {1905.13662},
  timestamp = {Mon, 03 Jun 2019 13:42:33 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1905-13662.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%DISENTANGLED REPRESENTATIONS 
@article{DBLP:journals/corr/abs-1905-01258,
  author    = {Francesco Locatello and
               Michael Tschannen and
               Stefan Bauer and
               Gunnar R{\"{a}}tsch and
               Bernhard Sch{\"{o}}lkopf and
               Olivier Bachem},
  title     = {Disentangling Factors of Variation Using Few Labels},
  journal   = {CoRR},
  volume    = {abs/1905.01258},
  year      = {2019},
  url       = {http://arxiv.org/abs/1905.01258},
  archivePrefix = {arXiv},
  eprint    = {1905.01258},
  timestamp = {Mon, 27 May 2019 13:15:00 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1905-01258.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%DISENTANGLED REPRESENTATIONS 
@InProceedings{pmlr-v119-locatello20a,
  title = 	 {Weakly-Supervised Disentanglement Without Compromises},
  author =       {Locatello, Francesco and Poole, Ben and Raetsch, Gunnar and Sch{\"o}lkopf, Bernhard and Bachem, Olivier and Tschannen, Michael},
  booktitle = 	 {Proceedings of the 37th International Conference on Machine Learning},
  pages = 	 {6348--6359},
  year = 	 {2020},
  editor = 	 {III, Hal Daumé and Singh, Aarti},
  volume = 	 {119},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {7},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v119/locatello20a/locatello20a.pdf},
  url = 	 {http://proceedings.mlr.press/v119/locatello20a.html},
  abstract = 	 {Intelligent agents should be able to learn useful representations by observing changes in their environment. We model such observations as pairs of non-i.i.d. images sharing at least one of the underlying factors of variation. First, we theoretically show that only knowing how many factors have changed, but not which ones, is sufficient to learn disentangled representations. Second, we provide practical algorithms that learn disentangled representations from pairs of images without requiring annotation of groups, individual factors, or the number of factors that have changed. Third, we perform a large-scale empirical study and show that such pairs of observations are sufficient to reliably learn disentangled representations on several benchmark data sets. Finally, we evaluate our learned representations and find that they are simultaneously useful on a diverse suite of tasks, including generalization under covariate shifts, fairness, and abstract reasoning. Overall, our results demonstrate that weak supervision enables learning of useful disentangled representations in realistic scenarios.}
}

%DISENTANGLED REPRESENTATIONS 
@InProceedings{pmlr-v139-trauble21a,
  title = 	 {On Disentangled Representations Learned from Correlated Data},
  author =       {Tr{\"a}uble, Frederik and Creager, Elliot and Kilbertus, Niki and Locatello, Francesco and Dittadi, Andrea and Goyal, Anirudh and Sch{\"o}lkopf, Bernhard and Bauer, Stefan},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {10401--10412},
  year = 	 {2021},
  editor = 	 {Meila, Marina and Zhang, Tong},
  volume = 	 {139},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {7},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v139/trauble21a/trauble21a.pdf},
  url = 	 {http://proceedings.mlr.press/v139/trauble21a.html},
  abstract = 	 {The focus of disentanglement approaches has been on identifying independent factors of variation in data. However, the causal variables underlying real-world observations are often not statistically independent. In this work, we bridge the gap to real-world scenarios by analyzing the behavior of the most prominent disentanglement approaches on correlated data in a large-scale empirical study (including 4260 models). We show and quantify that systematically induced correlations in the dataset are being learned and reflected in the latent representations, which has implications for downstream applications of disentanglement such as fairness. We also demonstrate how to resolve these latent correlations, either using weak supervision during training or by post-hoc correcting a pre-trained model with a small number of labels.}
}

%DISENTANGLED REPRESENTATIONS 
@article{DBLP:journals/corr/abs-2010-14407,
  author    = {Andrea Dittadi and
               Frederik Tr{\"{a}}uble and
               Francesco Locatello and
               Manuel W{\"{u}}thrich and
               Vaibhav Agrawal and
               Ole Winther and
               Stefan Bauer and
               Bernhard Sch{\"{o}}lkopf},
  title     = {On the Transfer of Disentangled Representations in Realistic Settings},
  journal   = {CoRR},
  volume    = {abs/2010.14407},
  year      = {2020},
  url       = {https://arxiv.org/abs/2010.14407},
  archivePrefix = {arXiv},
  eprint    = {2010.14407},
  timestamp = {Mon, 02 Nov 2020 18:17:09 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2010-14407.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

%GMM + HMM CLUSTERING REGIMES + 850, 700, 500, slp hPa
@article{article,
author = {Vrac, Mathieu and Hayhoe, Katharine and Stein, Michael},
year = {2007},
month = {04},
pages = {603 - 620},
title = {Identification of intermodal comparison of seasonal circulation patterns over North America},
volume = {27},
journal = {International Journal of Climatology},
doi = {10.1002/joc.1422}
}

%GMM CLUSTERING REGIMES + geography US + 700 hPa
@article {MultipleRegimesinNorthernHemisphereHeightFieldsviaMixtureModelClustering,
      author = "Padhraic Smyth and Kayo Ide and Michael Ghil",
      title = "Multiple Regimes in Northern Hemisphere Height Fields via Mixture Model Clustering",
      journal = "Journal of the Atmospheric Sciences",
      year = "1999",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      volume = "56",
      number = "21",
      doi = "10.1175/1520-0469(1999)056<3704:MRINHH>2.0.CO;2",
      pages=      "3704 - 3723",
      url = "https://journals.ametsoc.org/view/journals/atsc/56/21/1520-0469_1999_056_3704_mrinhh_2.0.co_2.xml"
}

%DPMM
@article{10.1214/06-BA104,
author = {David M. Blei and Michael I. Jordan},
title = {{Variational inference for Dirichlet process mixtures}},
volume = {1},
journal = {Bayesian Analysis},
number = {1},
publisher = {International Society for Bayesian Analysis},
pages = {121 -- 143},
keywords = {Bayesian computation, Dirichlet processes, hierarchical models, image processing, variational inference},
year = {2006},
doi = {10.1214/06-BA104},
URL = {https://doi.org/10.1214/06-BA104}
}


%NAOs QUANTIFICATION ENERGY VARIABLES
@article{10.31223/osf.io/8sntx,
author = {De Felice, Matteo and Dubus, Laurent and Suckling, Emma and Troccoli, Alberto},
year = {2018},
month = {07},
pages = {},
title = {The impact of the North Atlantic Oscillation on European hydro-power generation},
doi = {10.31223/osf.io/8sntx}
}

%NAOs QUANTIFICATION ENERGY VARIABLES
@article{10.1175/JAMC-D-12-0257.1,
author = {Jerez, Sonia and Trigo, Ricardo and Vicente-Serrano, Sergio and Pozo-Vazquez, D. and Lorente-Plazas, Raquel and Lorenzo-Lacruz, Jorge and Santos-Alamillos, Francisco and Montávez, J.},
year = {2013},
month = {10},
pages = {2204-2225},
title = {The Impact of the North Atlantic Oscillation on Renewable Energy Resources in Southwestern Europe},
volume = {52},
journal = {Journal of Applied Meteorology and Climatology},
doi = {10.1175/JAMC-D-12-0257.1}
}

%--------------------------------------------------
%geography regimes - US
@article { LargeScaleWeatherRegimesandLocalClimateovertheWesternUnitedStates,
      author = "Andrew W. Robertson and Michael Ghil",
      title = "Large-Scale Weather Regimes and Local Climate over the Western United States",
      journal = "Journal of Climate",
      year = "1999",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      volume = "12",
      number = "6",
      doi = "10.1175/1520-0442(1999)012<1796:LSWRAL>2.0.CO;2",
      pages=      "1796 - 1813",
      url = "https://journals.ametsoc.org/view/journals/clim/12/6/1520-0442_1999_012_1796_lswral_2.0.co_2.xml"
}

% geography regimes - ASIA
@article{asia,
author = {Bruyère, Cindy and Raktham, Chainarong and Done, J and Kreasuwun, J and Thongbai, J and Promnopas, Wonchai},
year = {2016},
month = {01},
pages = {},
title = {Major weather regime changes over Southeast Asia in a near-term future scenario},
volume = {72},
journal = {Climate Research},
doi = {10.3354/cr01442}
}

%seasons regimes
@article{season,
author = {Cortesi, Nicola and Torralba, Verónica and Lledo, Llorenç and Manrique-Suñén, Andrea and Gonzalez-Reviriego, Nube and Soret, Albert and Doblas-Reyes, Francisco},
year = {2021},
month = {06},
pages = {},
title = {Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability},
volume = {56},
journal = {Climate Dynamics},
doi = {10.1007/s00382-021-05679-y}
}

%cassout et al. summer regimes
@article{summer_regimes_cassou,
author = {Cassou, Christophe and Terray, Laurent and Phillips, Adam},
year = {2005},
month = {08},
pages = {2805-2811},
title = {Tropical Atlantic Influence on European Heat Waves},
volume = {18},
journal = {Journal of Climate - J CLIMATE},
doi = {10.1175/JCLI3506.1}
} 

%modeling choices: HMM, Probabilistic Models
@article{https://doi.org/10.1002/2016RG000538,
author = {Stan, Cristiana and Straus, David M. and Frederiksen, Jorgen S. and Lin, Hai and Maloney, Eric D. and Schumacher, Courtney},
title = {Review of Tropical-Extratropical Teleconnections on Intraseasonal Time Scales},
journal = {Reviews of Geophysics},
volume = {55},
number = {4},
pages = {902-937},
keywords = {tropical convection, NAO, PNA, high-impact weather},
doi = {https://doi.org/10.1002/2016RG000538},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2016RG000538},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2016RG000538},
abstract = {Abstract The interactions and teleconnections between the tropical and midlatitude regions on intraseasonal time scales are an important modulator of tropical and extratropical circulation anomalies and their associated weather patterns. These interactions arise due to the impact of the tropics on the extratropics, the impact of the midlatitudes on the tropics, and two-way interactions between the regions. Observational evidence, as well as theoretical studies with models of complexity ranging from the linear barotropic framework to intricate Earth system models, suggest the involvement of a myriad of processes and mechanisms in generating and maintaining these interconnections. At this stage, our understanding of these teleconnections is primarily a collection of concepts; a comprehensive theoretical framework has yet to be established. These intraseasonal teleconnections are increasingly recognized as an untapped source of potential subseasonal predictability. However, the complexity and diversity of mechanisms associated with these teleconnections, along with the lack of a conceptual framework to relate them, prevent this potential predictability from being translated into realized forecast skill. This review synthesizes our progress in understanding the observed characteristics of intraseasonal tropical-extratropical interactions and their associated mechanisms, identifies the significant gaps in this understanding, and recommends new research endeavors to address the remaining challenges.},
year = {2017}
}

%New ones
@article{yearround,
author = {Büeler, Dominik and Ferranti, L. and Magnusson, Linus and Quinting, Julian and Grams, Christian},
year = {2021},
month = {09},
pages = {},
title = {Year‐round sub‐seasonal forecast skill for Atlantic‐European weather regimes},
journal = {Quarterly Journal of the Royal Meteorological Society},
doi = {10.1002/qj.4178}
}

@article{extreme,
author = {Yiou, P. and Nogaj, M},
year = {2004},
month = {04},
pages = {},
title = {Extreme climatic events and weather regimes over the North Atlantic: When and where?},
volume = {31},
journal = {Geophys. Res. Lett},
doi = {10.1029/2003GL019119}
}

@article {Vautard1988,
      author = "R.  Vautard",
      title = "Multiple Weather Regimes over the North Atlantic: Analysis of Precursors and Successors",
      journal = "Monthly Weather Review",
      year = "1990",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      volume = "118",
      number = "10",
      doi = "10.1175/1520-0493(1990)118<2056:MWROTN>2.0.CO;2",
      pages=      "2056 - 2081",
      url = "https://journals.ametsoc.org/view/journals/mwre/118/10/1520-0493_1990_118_2056_mwrotn_2_0_co_2.xml"
}

@article { WeatherRegimeTransitionsandtheInterannualVariabilityoftheNorthAtlanticOscillationPartIALikelyConnection,
      author = "Dehai Luo and Jing Cha and Steven B. Feldstein",
      title = "Weather Regime Transitions and the Interannual Variability of the North Atlantic Oscillation. Part I: A Likely Connection",
      journal = "Journal of the Atmospheric Sciences",
      year = "2012",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      volume = "69",
      number = "8",
      doi = "10.1175/JAS-D-11-0289.1",
      pages=      "2329 - 2346",
      url = "https://journals.ametsoc.org/view/journals/atsc/69/8/jas-d-11-0289.1.xml"
}

@online{meteofrance,
    author = {Meteo-France},
    title = {Climate monitoring - Daily monitoring of weather regimes},
    Lastchecked = {01.12.2021},
    url = {http://seasonal.meteo.fr/}
}

@online{naoindex,
    author = {{Climate Prediction Center}},
    title = {Climate Prediction Center -  Monthly North Atlantic Oscillation Index},
    year = {},
    Lastchecked = {01.12.2021},
    url = https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao_index.html,
}

@article{Ferranti2015,
author = {Ferranti, Laura and Corti, Susanna and Janousek, Martin},
title = {Flow-dependent verification of the ECMWF ensemble over the Euro-Atlantic sector},
journal = {Quarterly Journal of the Royal Meteorological Society},
volume = {141},
number = {688},
pages = {916-924},
keywords = {flowdependent forecast skill, ensemble prediction system, Euro-Atlantic weather regime transitions, spread–error relationship, Euro-Atlantic blocking, North Atlantic Oscillation},
doi = {https://doi.org/10.1002/qj.2411},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.2411},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2411},
abstract = {In this article the concept of weather regimes is used to assess the flow-dependent skill of the European Centre for Medium-range Weather Forecast (ECMWF) ensemble predictions at the late medium-range. The flow patterns leading to more or less accurate predictions are identified and the variations of skill in these situations are quantified. The focus is on the Euro-Atlantic sector during the extended winter period when the atmospheric regime structure is most pronounced. Verification results show that, in the medium range, forecasts initiated in the negative phase of North Atlantic Oscillation (NAO−) are the most skillful. For these forecasts the ensemble spread over Europe is lower than average, showing that the ensemble spread provides useful information about the error of the ensemble-mean forecast. The performance of the ensemble is further assessed by stratifying the cases according to their initial conditions, as well as by their accuracy at forecast day 10. Results indicate that the least skillful predictions are mainly associated with missing the transitions to a blocking regime circulation. Forecasts also underestimate the blocking persistence, whereas they overestimate the persistence of zonal flows. Transitions to a positive phase of the NAO are also overrepresented.},
year = {2015}
}


@article{https://doi.org/10.1002/wea.3966,
author = {Lee, Simon H.},
title = {The January 2021 sudden stratospheric warming},
journal = {Weather},
volume = {76},
number = {4},
pages = {135-136},
doi = {https://doi.org/10.1002/wea.3966},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/wea.3966},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/wea.3966},
abstract = {On 5 January 2021, the Arctic stratospheric polar vortex dramatically weakened, and the temperature of the Arctic stratosphere rapidly increased in an event known as a major sudden stratospheric warming (SSW). It is likely that this SSW influenced surface weather conditions for over a month afterward.},
year = {2021}
}

@article{Domeisen,
author = {Domeisen, Daniela and Butler, Amy},
year = {2020},
month = {12},
pages = {},
title = {Stratospheric drivers of extreme events at the Earth’s surface},
volume = {1},
journal = {Communications Earth & Environment},
doi = {10.1038/s43247-020-00060-z}
}

@article{Doss_Gollin_2021,
	doi = {10.1088/1748-9326/ac0278},
	url = {https://doi.org/10.1088/1748-9326/ac0278},
	year = 2021,
	month = {6},
	publisher = {{IOP} Publishing},
	volume = {16},
	number = {6},
	pages = {064056},
	author = {James Doss-Gollin and David J Farnham and Upmanu Lall and Vijay Modi},
	title = {How unprecedented was the February 2021 Texas cold snap?},
	journal = {Environmental Research Letters},
	abstract = {Winter storm Uri brought severe cold to the southern United States in February 2021, causing a cascading failure of interdependent systems in Texas where infrastructure was not adequately prepared for such cold. In particular, the failure of interconnected energy systems restricted electricity supply just as demand for heating spiked, leaving millions of Texans without heat or electricity, many for several days. This motivates the question: did historical storms suggest that such temperatures were known to occur, and if so with what frequency? We compute a temperature-based proxy for heating demand and use this metric to answer the question ‘what would the aggregate demand for heating have been had historic cold snaps occurred with today’s population?’. We find that local temperatures and the inferred demand for heating per capita across the region served by the Texas Interconnection were more severe during a storm in December 1989 than during February 2021, and that cold snaps in 1951 and 1983 were nearly as severe. Given anticipated population growth, future storms may lead to even greater infrastructure failures if adaptive investments are not made. Further, electricity system managers should prepare for trends in electrification of heating to drive peak annual loads on the Texas Interconnection during severe winter storms.}
}


@article{Ferranti2018,
author = {Ferranti, Laura and Magnusson, Linus and Vitart, Frédéric and Richardson, David S.},
title = {How far in advance can we predict changes in large-scale flow leading to severe cold conditions over Europe?},
journal = {Quarterly Journal of the Royal Meteorological Society},
volume = {144},
number = {715},
pages = {1788-1802},
keywords = {blocking, Euro-Atlantic regime transitions, large-scale flow, North Atlantic Oscillation, severe cold conditions, subseasonal predictions},
doi = {https://doi.org/10.1002/qj.3341},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3341},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3341},
abstract = {The potential of early warning for severe cold conditions is explored using the Subseasonal to Seasonal (S2S) Prediction research project data archive. We explore the use of a two-dimensional phase space based on the leading empirical orthogonal functions (EOFs) of mid-tropospheric flow computed over the Euro-Atlantic region in order to study the time evolution of flow patterns associated with high-impact temperature anomalies. We find that the phase space is an effective tool for monitoring predictions of regime transitions at medium and extended ranges. We show that a number of S2S systems have some skill in the prediction of cold spells over Europe, even beyond the medium range. In particular, the ECMWF (European Centre for Medium-Range Weather Forecasts) model represents well the observed preferential transition paths. We reveal that the impact of the Madden–Julian Oscillation (MJO) on the predictive skill of large-scale flow over Europe is asymmetric. The impact of the MJO on the Brier skill scores and reliability is significantly positive for predictions of the negative phase of the North Atlantic Oscillation (NAO): beyond week one, forecasts with the MJO in their initial state are significantly more reliable than forecasts with no MJO in their initial conditions. In contrast, the predictive skill for positive NAO shows little sensitivity to the MJO.},
year = {2018}
}

@article{WR700hPa,
author = {Hertig, Elke and Jacobeit, Jucundus},
title = {Variability of weather regimes in the North Atlantic-European area: past and future},
journal = {Atmospheric Science Letters},
volume = {15},
number = {4},
pages = {314-320},
keywords = {weather regimes, non-stationarities, climate change},
doi = {https://doi.org/10.1002/asl2.505},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/asl2.505},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/asl2.505},
abstract = {Abstract The concept of weather regimes represents a process-oriented method of organizing the varying states of the atmospheric circulation. We define weather regimes as preferred, or recurrent, circulation patterns. We use a suite of reanalysis products and general circulation model (GCM) simulations to assess the reproducibility and variability of the regimes. We find distinct variability of the regimes in observational periods as well as in future projections. Most notable is the high variability of the North Atlantic Oscillation (NAO) regime anomaly patterns in the GCM simulations which is not evident in reanalyses, and the substantial increase of variability regarding the frequency of occurrence of the Atlantic ridge regime and the NAO+ regime.},
year = {2014}
}

@article { WeatherRegimesRecurrenceandQuasiStationarity,
      author = "Paul-Antoine  Michelangeli and Robert  Vautard and Bernard  Legras",
      title = "Weather Regimes: Recurrence and Quasi Stationarity",
      journal = "Journal of Atmospheric Sciences",
      year = "1995",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      volume = "52",
      number = "8",
      doi = "10.1175/1520-0469(1995)052<1237:WRRAQS>2.0.CO;2",
      pages=      "1237 - 1256",
      url = "https://journals.ametsoc.org/view/journals/atsc/52/8/1520-0469_1995_052_1237_wrraqs_2_0_co_2.xml"
}

@article{Bloomfield2021,
author = {Bloomfield, Hannah and Brayshaw, David and Brayshaw, David and Gonzalez, Paula and Gonzalez, Paula and Charlton-Perez, Andrew},
year = {2021},
month = {05},
pages = {2259-2274},
title = {Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries},
volume = {13},
journal = {Earth System Science Data},
doi = {10.5194/essd-13-2259-2021}
}

@article{https://doi.org/10.1002/asl2.505,
author = {Hertig, Elke and Jacobeit, Jucundus},
title = {Variability of weather regimes in the North Atlantic-European area: past and future},
journal = {Atmospheric Science Letters},
volume = {15},
number = {4},
pages = {314-320},
keywords = {weather regimes, non-stationarities, climate change},
doi = {https://doi.org/10.1002/asl2.505},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/asl2.505},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/asl2.505},
abstract = {Abstract The concept of weather regimes represents a process-oriented method of organizing the varying states of the atmospheric circulation. We define weather regimes as preferred, or recurrent, circulation patterns. We use a suite of reanalysis products and general circulation model (GCM) simulations to assess the reproducibility and variability of the regimes. We find distinct variability of the regimes in observational periods as well as in future projections. Most notable is the high variability of the North Atlantic Oscillation (NAO) regime anomaly patterns in the GCM simulations which is not evident in reanalyses, and the substantial increase of variability regarding the frequency of occurrence of the Atlantic ridge regime and the NAO+ regime.},
year = {2014}
}

@article{Bueler,
author = {Büeler, Dominik and Beerli, Remo and Wernli, Heini and Grams, Christian M.},
title = {Stratospheric influence on ECMWF sub-seasonal forecast skill for energy-industry-relevant surface weather in European countries},
journal = {Quarterly Journal of the Royal Meteorological Society},
volume = {146},
number = {733},
pages = {3675-3694},
keywords = {energy, European countries, polar vortex, stratosphere, sub-seasonal forecast skill, sudden stratospheric warming, surface weather},
doi = {https://doi.org/10.1002/qj.3866},
url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3866},
eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3866},
abstract = {Abstract Meteorologists in the energy industry increasingly draw upon the potential for enhanced sub-seasonal predictability of European surface weather following anomalous states of the winter stratospheric polar vortex (SPV). How the link between the SPV and the large-scale tropospheric flow translates into forecast skill for surface weather in individual countries – a spatial scale that is particularly relevant for the energy industry – remains an open question. Here we quantify the effect of anomalously strong and weak SPV states at forecast initial time on the probabilistic extended-range reforecast skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) in predicting country- and month-ahead-averaged anomalies of 2 m temperature, 10 m wind speed, and precipitation. After anomalous SPV states, specific surface weather anomalies emerge, which resemble the opposing phases of the North Atlantic Oscillation. We find that forecast skill is, to first order, only enhanced for countries that are entirely affected by these anomalies. However, the model has a flow-dependent bias for 2 m temperature (T2M): it predicts the warm conditions in Western, Central and Southern Europe following strong SPV states well, but is overconfident with respect to the warm anomaly in Scandinavia. Vice versa, it predicts the cold anomaly in Scandinavia following weak SPV states well, but struggles to capture the strongly varying extent of the cold air masses into Central and Southern Europe. This tends to reduce skill (in some cases significantly) for Scandinavian countries following strong SPV states, and most pronounced, for many Central, Southern European, and Balkan countries following weak SPV states. As most of the weak SPV states are associated with sudden stratospheric warmings (SSWs), our study thus advices particular caution when interpreting sub-seasonal regional T2M forecasts following SSWs. In contrast, it suggests that the model benefits from enhanced predictability for a considerable part of Europe following strong SPV states.},
year = {2020}
}
